Orbital Depot Location Optimization for Satellite Constellation Servicing with Low-Thrust Transfers

Author(s)
Choi, Euihyeon
Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
Series
Supplementary to:
Abstract
This paper addresses the critical problem of co-optimizing the optimal locations for orbital depots and the sequence of in-space servicing for a satellite constellation. While most traditional studies used network optimization for this problem, assuming a fixed set of discretized nodes in the network (i.e., a limited number of depot location candidates), this work is unique in that it develops a method to optimize the depot location in continuous space. The problem is formulated as mixed-integer nonlinear programming, and we propose a solution methodology that iteratively solves two decoupled problems: one using mixed-integer linear programming and the other using nonlinear programming with an analytic transfer solution. To demonstrate the effectiveness of our approach, we apply this methodology to a case study involving a GPS satellite constellation. Numerical experiments confirm the stability of our proposed solutions.
Sponsor
This work was conducted with support from the Air Force Office of Scientific Research (AFOSR), as part of the Space University Research Initiative (SURI), under award number FA9550-23-1-0723.
Date
2025
Extent
Resource Type
Text
Resource Subtype
Post-print
Rights Statement
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